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--- title: 'Tutorial: Python Function with Azure Blob Storage as input' description: Learn how you can connect a Python function to a storage blob as input using Service Connector in Azure. author: houk-ms ms.author: honc ms.service: service-connector ms.custom: devx-track-python ms.topic: tutorial ms.date: 12/05/2025 #customer intent: As a developer, I want to configure a Python function with Storage Blob as input function binding so that I can process and manage large volumes of data stored in Azure Blob Storage. --- # Tutorial: Python function with Azure Blob Storage as input In this tutorial, you learn how to configure a Python function with Azure Blob storage as input by completing the following tasks: > [!div class="checklist"] > * Use Visual Studio Code to create a Python function project. > * Change codes to add storage blob input function binding. > * Use Visual Studio Code to run the function locally. > * Use the Azure CLI to create a connection between Azure Function and Storage Blob with Service Connector. > * Use Visual Studio to deploy your function. An overview of the function project components in this tutorial: | Project Component | Selection / Solution | | ------------------------ | ------------------------------------ | | Source Service | Azure Function | | Target Service | Azure Storage Blob | | Function Binding | HTTP trigger, Storage Blob as Input | | Local Project Auth Type | Connection String | | Cloud Function Auth Type | System-Assigned Managed Identity | > [!WARNING] > Microsoft recommends that you use the most secure authentication flow available. The authentication flow described in this procedure requires a high degree of trust in the application, and carries risks that aren't present in other flows. You should only use this flow when other more secure flows, such as managed identities, aren't viable. ## Prerequisites - Install [Visual Studio Code](https://code.visualstudio.com) on one of the [supported platforms](https://code.visualstudio.com/docs/supporting/requirements#_platforms). - Azure CLI. You can use it in [Azure Cloud Shell](https://shell.azure.com/) or [install it locally](/cli/azure/install-azure-cli). - An Azure Storage Account and a Storage blob. If you don't have an Azure Storage account, [create one](../storage/common/storage-account-create.md). - This guide assumes you know the concepts presented in the [Functions developer guide](../azure-functions/functions-reference.md) and [how to connect to services in Functions](../azure-functions/add-bindings-existing-function.md). ## Create a Python function project Follow the [tutorial to create a local Azure Functions project](../azure-functions/how-to-create-function-vs-code.md?pivot=programming-language-python?pivots=python-mode-configuration#create-an-azure-functions-project). Provide the following information at the prompts: | Prompt | Selection | | --------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------- | | **Select a language** | Choose `Python`. (v1 programming language model) | | **Select a Python interpreter to create a virtual environment** | Choose your preferred Python interpreter. If an option isn't shown, type in the full path to your Python binary. | | **Select a template for your project's first function** | Choose `HTTP trigger`. | | **Provide a function name** | Enter `BlobStorageInputFunc`. | | **Authorization level** | Choose `Anonymous`, which lets anyone call your function endpoint.  | With this information, Visual Studio Code generates a Python function project with an HTTP trigger. ## Add a Blob Storage input binding Binding attributes are defined in the *function.json* file for a given function. To create a binding, right-click the `function.json` file in your function folder and choose **Add binding...**. Follow the prompts to define the following binding properties for the new binding: | Prompt | Value | Description | | ------------------------------------------------------------------------------- | --------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **Select binding direction** | `in` | The binding is an input binding. | | **Select binding with direction...** | `Azure Blob Storage` | The binding is an Azure Storage blob binding. | | **The name used to identify this binding in your code** | `inputBlob` | Name that identifies the binding parameter referenced in your code. | | **The path within your storage account from which the blob will be read** | `testcontainer/test.txt` | The blob path your function read as input. Prepare a file named `test.txt`, with a `Hello, World!` as the file content. Create a container named `testcontainer `, and upload the file to the container. | | **Select setting from "local.setting.json"** | `Create new local app settings` | Select the Storage Account your function reads as input. Visual Studio Code retrieves its connection string for the local project connection. | To check the binding was added successfully, 1. Open the `BlobStorageInputFunc/function.json` file, and check that a new binding with `type: blob` and `direction: in` was added into this file. 1. Open the `local.settings.json` file, and check that a new key-value pair `<your-storage-account-name>_STORAGE: <your-storage-account-connection-string>` that contains your storage account connection string was added into this file. After the binding is added, update your function code to consume the binding by replacing the `BlobStorageInputFunc/__init__.py` file with the following Python file: ```python import logging import azure.functions as func def main(req: func.HttpRequest, inputBlob: bytes) -> func.HttpResponse: logging.info('Python HTTP trigger function processed a request.') return func.HttpResponse('The triggered function executed successfully. And read blob content: {}'.format(inputBlob)) ``` ## Run the function locally Follow the [tutorial](../azure-functions/how-to-create-function-vs-code.md?pivot=programming-language-python?pivots=python-mode-configuration#run-the-function-locally) to run the function locally and verify the blob input. 1. If you're prompted to connect to storage, select the storage account you chose when creating the Azure Function resource. This storage account is used for Azure Function's internal use, and isn't necessarily the same as the storage account you use for the input. 1. To start the function locally, press <kbd>F5</kbd> or select the **Run and Debug** icon in the left-hand side Activity bar. 1. To verify the function can read the blob, right-click `Execute Function Now...` on the function in the Visual Studio Code **WORKSPACE** and check the function response. The response message should contain the content in your blob file. ## Create a connection using Service Connector In the last step, you ran the function locally and verified that your local project connects to your storage blob using a connection string. Next, you learn how to configure the connection between the Azure Function and Azure Blob Storage. Once your function is deployed to the cloud, this connection allows your function to read the blob. Then, in the cloud environment, we demonstrate how to authenticate using a system-assigned managed identity. 1. Open the `function.json` file in your local project, and change the value of the `connection` property in `bindings` to be `MyBlobInputConnection`. 1. Run the following Azure CLI command to create a connection between your Azure Function and your Azure Storage. ```azurecli az functionapp connection create storage-blob --source-id "<your-function-resource-id>" --target-id "<your-storage-blob-resource-id>" --system-identity --customized-keys AZURE_STORAGEBLOB_RESOURCEENDPOINT=MyBlobInputConnection__serviceUri ``` * `--source-id` format: `/subscriptions/{subscription}/resourceGroups/{source_resource_group}/providers/Microsoft.Web/sites/{site}` * `--target-id` format: `/subscriptions/{subscription}/resourceGroups/{target_resource_group}/providers/Microsoft.Storage/storageAccounts/{account}/blobServices/default` This step creates a connection between Azure Function and Azure Blob Storage using Service Connector, with a system-assigned managed identity. Service Connector configured a `MyBlobInputConnection__serviceUri` variable in the function's app settings used by the function binding runtime to connect to the storage, so that the function can read data from the blob storage. You can learn more about [how Service Connector helps Azure Functions connect to services](./how-to-use-service-connector-in-function.md). ## Deploy your function to Azure Now you can deploy your function to Azure and verify that the storage blob input binding works. 1. Follow the [tutorial](../azure-functions/how-to-create-function-vs-code.md?pivot=programming-language-python?pivots=python-mode-configuration#deploy-the-project-to-azure) to deploy your function to Azure. 1. To verify the function can read the blob, right-click `Execute Function Now...` on the function in the Visual Studio Code **RESOURCES** view and check the function response. The response message should contain the content in your blob file. ## Troubleshoot If there are any errors related with storage host, such as `No such host is known (<account-name>.blob.core.windows.net:443)`, you need to check whether the connection string you use to connect to Azure Storage contains the blob endpoint or not. If it doesn't, go to Azure Storage in the Azure portal, copy the connection string from the `Access keys` tab, and replace the values. If the error happens when you start the project locally, check the `local.settings.json` file. If the error happens when you deploy your function to the cloud (in this case, function deployment usually fails on `Syncing triggers`), check your function's App Settings. ## Clean up resources If you're not going to continue to use this project, delete the Function App resource you created earlier. ### [Portal](#tab/azure-portal) 1. In the Azure portal, open the Function App resource and select **Delete**. 1. Enter the app name and select **Delete** to confirm. ### [Azure CLI](#tab/azure-cli) Run the following command in the Azure CLI and replace all placeholders with your own information. ```azurecli az functionapp delete --name <function-name> --resource-group <resource-group> ``` --- ## Next steps Read the following articles to learn more about Service Connector concepts and how it helps Azure Functions connect to other cloud services. > [!div class="nextstepaction"] > [Learn about Service Connector concepts](./concept-service-connector-internals.md) > [!div class="nextstepaction"] > [Use Service Connector to connect Azure Functions to other services](./how-to-use-service-connector-in-function.md)